Today, there are inexpensive sensors that can collect data, including image data, and store that data in a computer readable format. One example of such a sensor is the CCD image sensor. Software programs can then access the stored data and manipulate and process the data to extract useful information.
The low cost of these sensors and the ready availability of computer programs to process data generated from these sensors has led to a host of new applications and devices, including inexpensive video cameras suited to videophone and image capture applications.
One disadvantage of these low cost devices has been the limited field-of-view they cover. Given their low cost, engineers have attempted to use multiple sensors to increase the field of view. However, as each sensor captures a separate field of view, any system that employs multiple sensors, must also have a system that integrates the different fields-of-view together to create one image or one set of data. Unfortunately, integrating multiple fields-of-view into a single composite data set is not a trivial exercise. The software to identify gaps and overlaps can be quite complex and expensive. Systems that precisely align the sensors to reduce overlap or gaps are costly to manufacture and thus defeat the purpose of using the low cost sensors.
Additionally, other prior art systems include very wide angle lens which are corrected by image processing operations. In this way a panoramic view may be created. However, such systems are costly and the efficacy of the image correction can vary depending upon the field of depth of the image.
Thus, there is a need for an efficient and inexpensive system that can allow multiple sensors to work together to provide a composite image presenting an enlarged field-of-view.